Estimate forest carbon stock from remote sensing data using BEF, allometric equations, or IPCC Tier 1/2 methods. Includes Monte Carlo uncertainty analysis. Supports raster (GeoTIFF) and tabular (CSV) inputs.
编程
geoskill-carbon-stock-estimation
试用由 NDVI 幂律异速生长方程估算地上生物量碳,叠加根茎比地下碳与类型化土壤碳密度。Estimates carbon stocks from biomass allometry and soil carbon density. 输出地上碳/土壤碳/总碳三张 GeoTIFF 与汇总 JSON。
它能做什么
由 NDVI 幂律异速生长方程估算地上生物量碳,叠加根茎比地下碳与类型化土壤碳密度。Estimates carbon stocks from biomass allometry and soil carbon density. 输出地上碳/土壤碳/总碳三张 GeoTIFF 与汇总 JSON。
技能文档
碳储量估算 | Carbon Stock Estimation
Aboveground biomass is estimated with the power-law allometric equation AGB = scale × max(NDVI, 0)^power and multiplied by the IPCC default carbon fraction of 0.47 to obtain aboveground carbon; belowground carbon = aboveground carbon × root-to-shoot ratio (default 0.30); soil organic carbon is computed from five land cover classes — forest/grassland/cropland/bare land/water — with carbon densities of 60/45/35/15/0 Mg C/ha × pixel area. Total carbon = aboveground carbon × (1 + root-to-shoot ratio) + soil carbon.
Applicable scenarios: regional carbon baseline accounting, dual-carbon (carbon peak and carbon neutrality) target assessment, and measurement of ecological carbon sequestration projects.
Dependencies / 依赖
pip install numpy rasterio
Usage / 使用方法
Example 1: Synthetic Scene with Default Parameters
python geoskill-carbon-stock-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output
Example 2: Real NDVI Raster (band1 Must Be NDVI, Values ≈ −1..1)
python geoskill-carbon-stock-estimation.py --input ndvi.tif --output-dir ./real
Example 3: Custom Allometric Equation Parameters
python geoskill-carbon-stock-estimation.py --bbox 116 39 117 40 --synthetic --scale 150 --power 1.8 --output-dir ./tuned
Example 4: Different Region
python geoskill-carbon-stock-estimation.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai
Example 5: Quiet Batch Mode
python geoskill-carbon-stock-estimation.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch
Output / 输出
| File | Format | Description |
|---|---|---|
agb_carbon.tif | GeoTIFF (float32) | Aboveground biomass carbon (Mg C/pixel) |
soil_carbon.tif | GeoTIFF (float32) | Soil organic carbon (Mg C/pixel) |
total_carbon.tif | GeoTIFF (float32) | Total carbon stock (Mg C/pixel) |
carbon_params.json | JSON | Carbon fraction, root-to-shoot ratio, and totals of each carbon pool |
output-manifest.json | JSON | Run manifest (inputs/outputs/QA/software versions) |
Data Source / 数据源 / Source
Local GeoTIFF (band1=NDVI, values approximately −1..1; inputs outside this range are rejected with exit code 6); the carbon fraction (0.47) follows the IPCC 2006 Guidelines for National Greenhouse Gas Inventories, the root-to-shoot ratio follows the global meta-analysis of Mokany et al. 2006, and the soil carbon densities are order-of-magnitude defaults for the 0–30 cm soil layer (IPCC reference stock convention); synthetic mode generates data locally with no external data source.
Limitations / 局限(诚实声明)
AGB = scale × NDVI^poweris an empirical power-law model; scale/power must be calibrated by region and vegetation type, and the default values (200 / 2.0) are intended for screening-level estimates only and cannot be used directly for project-level accounting (MRV).- The 0.30 root-to-shoot ratio is a global default: in reality it varies by biome (tropical forests ~0.24, shrublands/grasslands higher), and fine-scale accounting should replace it with biome-specific values.
- The soil carbon densities (forest 60 / grassland 45 / cropland 35 / bare land 15 / water 0 Mg C/ha) are fixed defaults that are not refined by climate zone or soil type; surface litter and deadwood carbon pools are not included.
Privacy / 隐私声明 / Privacy
- Runs fully offline by default; makes no network requests
--syntheticmode reads no external data- All computation is performed locally; no user data is uploaded
License / License
MIT
name: geoskill-carbon-stock-estimation description: '由 NDVI 幂律异速生长方程估算地上生物量碳,叠加根茎比地下碳与类型化土壤碳密度。Estimates carbon stocks from biomass allometry and soil carbon density. 输出地上碳/土壤碳/总碳三张 GeoTIFF 与汇总 JSON。'
碳储量估算 | Carbon Stock Estimation
地上生物量按幂律异速方程 AGB = scale × max(NDVI,0)^power 估算,乘以 IPCC 默认含碳系数 0.47 得地上碳;地下碳 = 地上碳 × 根茎比(默认 0.30);土壤有机碳按林/草/耕/裸/水五类碳密度(60/45/35/15/0 Mg C/ha)× 像元面积。总碳 = 地上碳×(1+根茎比) + 土壤碳。
适用场景:区域碳本底核算、双碳目标评估、生态固碳项目计量。
依赖
pip install numpy rasterio
使用方法
示例 1:合成场景默认参数
python geoskill-carbon-stock-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output
示例 2:真实 NDVI 栅格(band1 必须为 NDVI,取值约 −1..1)
python geoskill-carbon-stock-estimation.py --input ndvi.tif --output-dir ./real
示例 3:自定义异速方程参数
python geoskill-carbon-stock-estimation.py --bbox 116 39 117 40 --synthetic --scale 150 --power 1.8 --output-dir ./tuned
示例 4:不同区域
python geoskill-carbon-stock-estimation.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai
示例 5:静默批量
python geoskill-carbon-stock-estimation.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch
输出
| 文件 | 格式 | 说明 |
|---|---|---|
agb_carbon.tif | GeoTIFF (float32) | 地上生物量碳(Mg C/像元) |
soil_carbon.tif | GeoTIFF (float32) | 土壤有机碳(Mg C/像元) |
total_carbon.tif | GeoTIFF (float32) | 总碳储量(Mg C/像元) |
carbon_params.json | JSON | 含碳系数、根茎比、各碳库总量 |
output-manifest.json | JSON | 运行清单(输入/输出/QA/软件版本) |
数据源 / Source
本地 GeoTIFF(band1=NDVI,取值约 −1..1;超出该范围的输入会被拒绝,exit 6); 含碳系数(0.47)参考 IPCC 2006 清单指南,根茎比参考 Mokany et al. 2006 全球元分析, 土壤碳密度为 0–30 cm 土层的量级默认值(IPCC 参考储量口径);合成模式本地生成,无外部数据源。
局限(诚实声明)
AGB = scale × NDVI^power为经验幂律模型,scale/power 需按区域/植被类型标定, 默认值(200 / 2.0)仅作筛查级估算,不能直接用于项目计量(MRV)。- 根茎比 0.30 为全球通用值:实际随生物区变化(热带林 ~0.24,灌丛/草地更高), 精细核算应替换为生物区特异值。
- 土壤碳密度(林 60 / 草 45 / 耕 35 / 裸 15 / 水 0 Mg C/ha)为固定默认值, 未按气候区/土类细化;地表凋落物与死木碳库未计入。
隐私声明 / Privacy
- 默认完全离线运行,不发起任何网络请求
--synthetic模式不读取任何外部数据- 所有计算在本地完成,不上传用户数据
License
MIT
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